3.2 Simulations of Climate Change Impacts during the last Decade Atmospheric external forcing fields: NCEP/NCAR reanalysis dataset for 1958-2007. We use the CORE.2 Global Air-Sea Flux dataset (Large and Yeager, 2004) available from http://dods.idris.fr/reee605/CORE2_interan/. The CORE.2 dataset consists of 8 variables used for interannual forcing: -6-hourly wind velocity components at 10m above the surface -6-hourly potential temperature at 2m above the surface -6-hourly specific humidity at 2m above the surface -daily solar and infra-red downwelling radiation at the surface -monthly total precipitation and snow falling rates. Biogeochemical data: We use various initial biogeochemical datasets described in Aumont and Bopp (2006). Biogeochemical datasets includes parameters such as Alkaline (Alk), Dissolved Inorganic Carbon (DIC), Nutrients (NO3, PO4, Si, Fer, NH4), Dissolved Organic Carbon (DOC) and O2. Model Spinup: One pass through the 1958-2007 forcing with the CORE.2 dataset will be used as a spinup for the simulations beginning at 01Jan1958. In this "spin-up" run, the ocean is initially at rest with temperature and salinity set to January climatorogical values of Levitus (1982). In the Arctic and Southern Oceans, initial mean sea ice thickness of 3.5 m is imposed in regions with a sea surface temperature below 0 C. An initial ice concentration of 0.95 are also assumed (Vancoppenolle, et al, 2009a). Initial biogeochemical parameters are also set following Aumont and Bopp (2006). From this initial state, the ORCA2_LIM2_PISCES configuration of NEMO is integrated for 50 years with Newtonian restoring terms for sea surface salinity only. For the ocean surface forcing, the CORE bulk formula is used with the 50-year CORE.2 dataset. For the initial conditions at 01Jan1958 in the 50-year 1958-2007 experiment, the restart conditions at the end of 2007 in the spinup run were used that include restart conditions of biogeochemical parameters and the model was forced with the 50-year CORE.2 dataset. The model results for the 40-year period 1968-2007 of this experiment are used to produce the figures. *========================================================================================= 2. Numerical Modeling 2.1 Model Description We use the ORCA2_LIM2_PISCES configuration of the NEMOGCM (Nucleus for European Modelling of the Ocean), a global ocean modeling framework which is composed of an ocean model ORCA2, coupled to an ice model LIM2, and a biogeochemichal model PISCES (Madec et al., 1999; Madec, 2008; http://www.nemo-ocean.eu/About-NEMO). Ocean model: ORCA2 is a primitive equation model adapted to regional and global ocean circulation problems. The distribution of variables is a three-dimensional Arakawa C-type grid. In the ORCA2_LIM2_PISCES configuration, the model domain extends from 78S to 90N. The model uses a global tripolar orthogonal curvilinear grid with 2 deg zonal resolution and a meridional resolution varying from 0.5 at the equator to 2 cos(phi) south of 20S. The horizontal grid features two points of convergence in the Northern Hemisphere, both situated on continents to overcome the North Pole singularity found for geographical meshes, thus avoids singularity point inside the computational domain (Madec and Imbard, 1996), and attains the ratio of anisotropy nearly one everywhere. Minimum resolution in high latitudes is about 65 km in the Arctic and 50 km in the Antarctic (Timmermann et al, 2005). In the vertical direction, the model uses a full or partial step z-coordinate, or s-coordinate. There are 31 levels, with 10 levels in the top 100m and partial steps in the lowest level. The vertical mesh is deduced from a mathematical function of z (Madec and Imbard, 1996). Bottom topography and coastlines are derived from the ETOPO5 dataset and Smith and Sandwell (1997). In the ORCA2_LIM2_PISCES configuration, lateral tracer mixing is done along isopycnals. Eddy induced tracer advection is parameterized following Gent and McWilliams (1990). Horizontal momentum is mixed along model level surfaces using the eddy viscosity coefficients varying with latitude, longitude and depth. Vertical eddy diffusivity and viscosity coefficients are calculated using a 1.5 order turbulent kinetic energy model (Gaspar et al., 1990). Zero fluxes of heat and salt and no-slip conditions are applied through lateral solid boundaries. At the bottom boundary, zero fluxes of heat and salt are applied through the ocean bottom. Among the process methods treating the penetrative solar radiation available in NEMO are the "bio-model" light penetration method and the "RGB" light penetration method. For the calculation of the phytoplankton light limitation as well as the oceanic heating rate due to the penetrative solar radiation, both mothods use a polychromatic (3-waveband) model called "RGB (Red-Green-Blue) model." It is a simplified version of the 61-waveband model proposed by Morel (1988) in which light absorption in the ocean is dependent of the particle concentration and is spectrally selective. The solar radiation in the wavelength range longer than 700 nm is strongly absorbed and contributes to heating the top few centimeters of the ocean. On the other hand, the solar radiation in shorter wavelenghts (400-700nm) propagates to deeper depths and contributes to local heating below the surface. In the "RGB model" implemented in NEMO, visible light is divided into three wavelengths blue (400-500 nm), green (500-600 nm) and red (600-700 nm). The RGB model reproduces the light penetration profiles quite closely those predicted by the full spectral model of Morel (1988) with much better computer efficiency (Lengaine et al, 2007; Lengaine et al, 2009). In the "bio-model" light penetration method implemented in NEMO, the chlorophyll concentration produced by the biological component in the biogeochemical PISCES model retroacts on the ocean heat budget by modulating the absorption of light via a polychromatic model, the RGB model, that is used to calculate the phytoplankton light limitation as well as the oceanic heating rate (Lengaigne et al., 2007). No external chlorophyll data is required in this method. In contrast, the "RGB" light penetration method in NEMO uses the observed monthly satellite chlorophyll field as input chlorophyll data with the RGB model to calculate the phytoplankton light limitation as well as the oceanic heating rate at the depth up to 400m deep. In this method, the chlorophyll concentration is still produced by the biological component in the biogeochemical PISCES model but it will not retroacts on the ocean heat budget by modulating the absorption of light. Sea-ice model: Within NEMO, the ocean is interfaced with the interactive sea-ice model LIM2 (Louvain-la-Neuve sea ice model) (Fichefet and Morales-Maqueda, 1997; Timmermann, et al, 2005). LIM2 is a C-grid dynamic-thermodynamic model that includes the representation of the subgrid-scale distributions of five-category sea ice thickness, enthalpy, salinity and age. Brine entrapment and drainage as well as brine impact on ice thermodynamics and a snow ice formation scheme are explicitly included (Vancoppenolle, et al, 2009a; Vancoppenolle, et al, 2009b). Biogeochemical model: The NEMO modeling framework includes PISCES based on the Hamburg Ocean Carbon Cycle 5 (HAMOCC5) model (Aumont et al., 2003; Aumont and Bopp, 2006) (see http://www.meece.eu/documents/deliverables/WP2/D2.4.pdf). PISCES is a biogeochemical model which simulates the marine biological productivity that describes the biogeochemical cycles of carbon and of the main nutrients (P, N, Si, Fe). PISCES assumes a constant Redfield ratio and phytoplankton growth is directly limited by the external availability in nutrients (Monod, 1942) so that the elemental ratios of Fe, Si and Chlorophyll (Chl) are prognostically predicted based on external concentrations of the limiting nutrients. PISCES has currently 24 compartments. These are five modeled limiting nutrients for phytoplankton growth: Nitrate and Ammonium, Phosphate, Silicate and Iron. Phosphate and Nitrate+Ammonium are not really independent nutrients in PISCES since they are linked by constant Redfield ratios but the nitrogen pool undergoes nitrogen fixation and denitrification. Four living compartments are represented: two phytoplankton size-classes/groups (nanophytplankton and diatoms) and two zooplankton size classes (microzooplankton and mesozooplankton). For phytoplankton, prognostic variables are total biomass, the iron, chlorophyll and silicon contents. This means that the Fe/C, Chl/C and Si/C ratios of both phytoplankton groups are fully predicted by the model. For zooplankton, only the total biomass is modeled. For all species, the O/C/N/P ratios are kept constant and are not allowed to vary.